2026-09-20T08:57:32Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/1157422026-06-17T14:43:03Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022

Ramesh Raskar. Kadambi, Achuta Program in Media Arts and Sciences (Massachusetts Institute of Technology) Program in Media Arts and Sciences (Massachusetts Institute of Technology) 2018-05-23T16:32:47Z 2018-05-23T16:32:47Z 2018 2018 http://hdl.handle.net/1721.1/115742 1036986780 Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 261-273). Understanding how light travels through macroscopic scenes can transform autonomous driving, medical imaging and consumer photography. Unfortunately, this understanding is difficult to achieve: trillions of light paths are measured by millions of pixels. The framework of computational light transport was introduced to model this complex interaction between light and matter in a tractable space. In this thesis, we study new methods to invoke space, time, and polarization into a computational light transport framework. First, we study how probing the time dimension enables cameras to separate bounces from multiple light paths. Our solutions are inspired by prior work on multipath in wireless and telecommunications. We then invoke both time and space to provide the first provable bound on resolution for seeing around corners or through scattering media. Finally, we jointly invoke space, time, and polarization to propose an ultra-high quality form of 3D imaging. This thesis contributes a few analytical theories, including: (1) provable bounds on multipath separation; (2) provable bounds on seeing around corners; and (3) proof of shape reconstruction from polarimetric measurements. The thesis also contributes new applications that span: (a) micron-scale 3D cameras; (b) real-time object tracking around corners; and (c) single-shot computational relighting of images. Future applications encompass equipping self-driving cars the ability to see through fog, or enabling doctors to see deeper inside the body using light. by Achuta Kadambi. Ph.D. 273 pages eng Massachusetts Institute of Technology MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 Program in Media Arts and Sciences () Computational light transport using space, time, and polarization Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="72dd513e-a370-45f7-a45b-306ec1b8e7d1"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Computational light transport using space, time, and polarization</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2018</PublicationDate> <Authors> <Author> <DisplayName>Kadambi, Achuta</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Program in Media Arts and Sciences ()</Keyword> <Abstract>Understanding how light travels through macroscopic scenes can transform autonomous driving, medical imaging and consumer photography. Unfortunately, this understanding is difficult to achieve: trillions of light paths are measured by millions of pixels. The framework of computational light transport was introduced to model this complex interaction between light and matter in a tractable space. In this thesis, we study new methods to invoke space, time, and polarization into a computational light transport framework. First, we study how probing the time dimension enables cameras to separate bounces from multiple light paths. Our solutions are inspired by prior work on multipath in wireless and telecommunications. We then invoke both time and space to provide the first provable bound on resolution for seeing around corners or through scattering media. Finally, we jointly invoke space, time, and polarization to propose an ultra-high quality form of 3D imaging. This thesis contributes a few analytical theories, including: (1) provable bounds on multipath separation; (2) provable bounds on seeing around corners; and (3) proof of shape reconstruction from polarimetric measurements. The thesis also contributes new applications that span: (a) micron-scale 3D cameras; (b) real-time object tracking around corners; and (c) single-shot computational relighting of images. Future applications encompass equipping self-driving cars the ability to see through fog, or enabling doctors to see deeper inside the body using light.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>